Integration of multiple fuzzy FP-trees

Authors:
Tzung-Pei Hong;Chun-Wei Lin;Tsung-Ching Lin;Yi-Fan Chen;Shing-Tai Pan
Affiliations:
Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan, R.O.C. and Department of Computer Science and Engineering, National Sun Yat-sen Uni ...;Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan, R.O.C.;Department of Applied Mathematics, National University of Kaohsiung, Kaohsiung, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan, R.O.C.
Venue:
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
Year:
2012

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Abstract

In the past, the MFFP-tree algorithm was proposed to handle the quantitative database for efficiently mining the complete fuzzy frequent itemsets. In this paper, we propose an integrated MFFP (called iMFFP)-tree algorithm for merging several individual MFFP trees into an integrated one. It can help derive global fuzzy rules among distributed databases, thus allowing managers to make more sophisticated decisions. Experimental results also showed the performance of the proposed approach.